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Time series forecasting is a decisive step in data modeling and a significant area in machine learning. This paper presents Long short-term memory (LSTM) network, a deep learning neural network for predicting Covid-19 cases in India. The neural network models are trained and tested with Covid-19 case data sets obtained from PRS Legislative Research database. Further, the parameter optimization is carried out for choosing the optimal network. The parameters considered for evaluating the performance of LSTM network are RMSE, number of epochs, accuracy and loss. The results are compared with various recurrent neural network models and autoregressive model. The results revealed an improved accuracy of 92.8% for LSTM network in predicting the transmission of Covid-19 in India. [ABSTRACT FROM AUTHOR]